1. Tutorial 1 Inferential Statistics, Statistical Modelling & Survey Methods (BS2506) Pairach Piboonrungroj(Champ)me@pairach.com

2. 1.(a) Pearson’s product moment correlation coefficient and test a significant positive correlation

3. 1.(a) Pearson’s product moment correlation coefficient and test a significant positive correlation

4. 1.(a) Pearson’s product moment correlation coefficient and test a significant positive correlation

5. 1.(a) Pearson’s product moment correlation coefficient and test a significant positive correlation

6. 1.a thus we reject H0

7. 1(b)

8. 1(c) Therefore do not reject the null hypothesis

9. 2(a)

10. 2(a)

11. 2(a)

12. 2(a)

13. 2(a)

14. 2(b) Reject H0. Therefore there is a significant correlation between the rankings.

15. 3. Wine’s Demand & Price

16. 3 (a)

17. 3.b. Regression Model

18. 3(b)

19. 3(b)

20. 3(b)

21. 3 (b) (a) If y = 0, x = 4.9 (b) If y = 500, x = 3.7 b a

22. 3(c) x = £3.50 then Estimated y = 2080-424(3.50)=596 C2.It is possiblebut NOT appropriate to use the above equation for a price of £1.99 because the sample data for this estimated linear regression equation included prices for £2.99 to £4.99.

23. 3(d) ESS = 2,661,569 – (2,080)(4,097) – (-424)(14,123) = 127,961 TSS = 2,661,569 – 10(409.7)2 = 983,028 R2 = 1 – 127,961/983,028 = 0.87 87% of Variation in Demand (y) is Explained by Price (x).

24. 3(e)

25. 3(f) Thus we reject H0. There is a negative relationship between price & demand.

26. 3(g) C.I.= -557 to -290

27. 3(h) C.I. for the mean = 487 to 705

28. 3(I) P.I. = 284 to 908

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